06 Fakultät Luft- und Raumfahrttechnik und Geodäsie
Permanent URI for this collectionhttps://elib.uni-stuttgart.de/handle/11682/7
Browse
9 results
Search Results
Item Open Access Making historical gyroscopes alive - 2D and 3D preservations by sensor fusion and open data access(2021) Fritsch, Dieter; Wagner, Jörg F.; Ceranski, Beate; Simon, Sven; Niklaus, Maria; Zhan, Kun; Mammadov, GasimThe preservation of cultural heritage assets of all kind is an important task for modern civilizations. This also includes tools and instruments that have been used in the previous decades and centuries. Along with the industrial revolution 200 years ago, mechanical and electrical technologies emerged, together with optical instruments. In the meantime, it is not only museums who showcase these developments, but also companies, universities, and private institutions. Gyroscopes are fascinating instruments with a history dating back 200 years. When J.G.F. Bohnenberger presented his machine to his students in 1810 at the University of Tuebingen, Germany, nobody could have foreseen that this fascinating development would be used for complex orientation and positioning. At the University of Stuttgart, Germany, a collection of 160 exhibits is available and in transition towards their sustainable future. Here, the systems are digitized in 2D, 2.5D, and 3D and are made available for a worldwide community using open access platforms. The technologies being used are computed tomography, computer vision, endoscopy, and photogrammetry. We present a novel workflow for combining voxel representations and colored point clouds, to create digital twins of the physical objects with 0.1 mm precision. This has not yet been investigated and is therefore pioneering work. Advantages and disadvantages are discussed and suggested work for the near future is outlined in this new and challenging field of tech heritage digitization.Item Open Access CRBeDaSet : a benchmark dataset for high accuracy close range 3D object reconstruction(2023) Gabara, Grzegorz; Sawicki, PiotrThis paper presents the CRBeDaSet - a new benchmark dataset designed for evaluating close range, image-based 3D modeling and reconstruction techniques, and the first empirical experiences of its use. The test object is a medium-sized building. Diverse textures characterize the surface of elevations. The dataset contains: the geodetic spatial control network (12 stabilized ground points determined using iterative multi-observation parametric adjustment) and the photogrammetric network (32 artificial signalized and 18 defined natural control points), measured using Leica TS30 total station and 36 terrestrial, mainly convergent photos, acquired from elevated camera standpoints with non-metric digital single-lens reflex Nikon D5100 camera (ground sample distance approx. 3 mm), the complex results of the bundle block adjustment with simultaneous camera calibration performed in the Pictran software package, and the colored point clouds (ca. 250 million points) from terrestrial laser scanning acquired using the Leica ScanStation C10 and post-processed in the Leica Cyclone™ SCAN software (ver. 2022.1.1) which were denoized, filtered, and classified using LoD3 standard (ca. 62 million points). The existing datasets and benchmarks were also described and evaluated in the paper. The proposed photogrammetric dataset was experimentally tested in the open-source application GRAPHOS and the commercial suites ContextCapture, Metashape, PhotoScan, Pix4Dmapper, and RealityCapture. As the first experience in its evaluation, the difficulties and errors that occurred in the software used during dataset digital processing were shown and discussed. The proposed CRBeDaSet benchmark dataset allows obtaining high accuracy (“mm” range) of the photogrammetric 3D object reconstruction in close range, based on a multi-image view uncalibrated imagery, dense image matching techniques, and generated dense point clouds.Item Open Access Evaluation of Phase One scan station for analogue aerial image digitisation(2021) Schulz, Joachim; Cramer, Michael; Herbst, TheresaHistorical aerial photographs represent a special cultural asset for preserving information about land cover and land use change in the twentieth century with a high spatial and temporal resolution. A current topic is the digitisation of historical images to make them accessible to a wider range of users and to preserve them from age deterioration. For a photogrammetric evaluation, a high geometric stability and accuracy during the digitization process is required. In this work, the resolving power and geometric quality of a Phase One iXM-MV150F high-performance camera was investigated, which is used at the Landesamt für Geoinformation und Landentwicklung Baden-Württemberg in the project ‘Digitaler Luftbildatlas Baden-Württemberg’ for the digitisation of historical aerial photographs. The resolving power of the system was empirically measured and analysed. The required modulation transfer function was determined using Siemens stars. With this method, the significant influence of the focus setting and deviations of the plane-parallel alignment could be determined. Using a digitised aerial survey of the Vaihingen/Enz test field, the impact of the above-mentioned effects and the influence of the geometry of the scanning camera on the quality of the derived data products was shown in comparison to a photogrammetric scanner. The comparison showed that dedicated photogrammetric scanners still achieve a higher accuracy, even if a high-quality optical system is used for the digitising stand with the document camera. Further investigations are justified to improve the accuracy and stability of digitising the aerial image with a document camera.Item Open Access Radargrammetric DSM generation by semi-global matching and evaluation of penalty functions(2022) Wang, Jinghui; Gong, Ke; Balz, Timo; Haala, Norbert; Sörgel, Uwe; Zhang, Lu; Liao, MingshengRadargrammetry is a useful approach to generate Digital Surface Models (DSMs) and an alternative to InSAR techniques that are subject to temporal or atmospheric decorrelation. Stereo image matching in radargrammetry refers to the process of determining homologous points in two images. The performance of image matching influences the final quality of DSM used for spatial-temporal analysis of landscapes and terrain. In SAR image matching, local matching methods are commonly used but usually produce sparse and inaccurate homologous points adding ambiguity to final products; global or semi-global matching methods are seldom applied even though more accurate and dense homologous points can be yielded. To fill this gap, we propose a hierarchical semi-global matching (SGM) pipeline to reconstruct DSMs in forested and mountainous regions using stereo TerraSAR-X images. In addition, three penalty functions were implemented in the pipeline and evaluated for effectiveness. To make accuracy and efficiency comparisons between our SGM dense matching method and the local matching method, the normalized cross-correlation (NCC) local matching method was also applied to generate DSMs using the same test data. The accuracy of radargrammetric DSMs was validated against an airborne photogrammetric reference DSM and compared with the accuracy of NASA’s 30 m SRTM DEM. The results show the SGM pipeline produces DSMs with height accuracy and computing efficiency that exceeds the SRTM DEM and NCC-derived DSMs. The penalty function adopting the Canny edge detector yields a higher vertical precision than the other two evaluated penalty functions. SGM is a powerful and efficient tool to produce high-quality DSMs using stereo Spaceborne SAR images.Item Open Access Concept and performance evaluation of a novel UAV-borne topo-bathymetric LiDAR sensor(2020) Mandlburger, Gottfried; Pfennigbauer, Martin; Schwarz, Roland; Flöry, Sebastian; Nussbaumer, LukasWe present the sensor concept and first performance and accuracy assessment results of a novel lightweight topo-bathymetric laser scanner designed for integration on Unmanned Aerial Vehicles (UAVs), light aircraft, and helicopters. The instrument is particularly well suited for capturing river bathymetry in high spatial resolution as a consequence of (i) the low nominal flying altitude of 50-150 m above ground level resulting in a laser footprint diameter on the ground of typically 10-30 cm and (ii) the high pulse repetition rate of up to 200 kHz yielding a point density on the ground of approximately 20-50 points/m2. The instrument features online waveform processing and additionally stores the full waveform within the entire range gate for waveform analysis in post-processing. The sensor was tested in a real-world environment by acquiring data from two freshwater ponds and a 500 m section of the pre-Alpine Pielach River (Lower Austria). The captured underwater points featured a maximum penetration of two times the Secchi depth. On dry land, the 3D point clouds exhibited (i) a measurement noise in the range of 1-3 mm; (ii) a fitting precision of redundantly captured flight strips of 1 cm; and (iii) an absolute accuracy of 2-3 cm compared to terrestrially surveyed checkerboard targets. A comparison of the refraction corrected LiDAR point cloud with independent underwater checkpoints exhibited a maximum deviation of 7.8 cm and revealed a systematic depth-dependent error when using a refraction coefficient of n = 1.36 for time-of-flight correction. The bias is attributed to multi-path effects in the turbid water column (Secchi depth: 1.1 m) caused by forward scattering of the laser signal at suspended particles. Due to the high spatial resolution, good depth performance, and accuracy, the sensor shows a high potential for applications in hydrology, fluvial morphology, and hydraulic engineering, including flood simulation, sediment transport modeling, and habitat mapping.Item Open Access Übertragungskette des optischen Bildaufnahmeprozesses bei Flug- und Satellitenaufnahmen(1986) Tiziani, Hans J.; Förstner, WolfgangDie Beurteilung des Informationsverlustes bei Abbildungen ist zentral für die Erkennbarkeit und präzise Lokalisierbarkeit von Objektdetails. Gute Bildqualität zeichnet sich durch scharfe Abbildung von Punkten und Kanten aus. Die Ermittlung der Bildqualität kann sich auf klassische Verfahren zur Bestimmung der Punktverwaschungsfunktion stützen. Die Entfaltung der Bildinformation mit der resultierenden Verwaschungsfunktion führt zur Bildverbesserung und zur Genauigkeitssteigerung bei der Punktbildzuordnung. Die Untersuchungen sollen auf den Nahbereich ausgedehnt werden - dies speziell im Hinblick auf die Vermessung und Navigation im Nahbereich. Dabei ist die Verwaschungsfunktion von bewegten und defokussierten Objekten von besonderer Bedeutung.Item Open Access Three- and four-dimensional topographic measurement and validation(2021) Rocca, Fabio; Li, Deren; Tebaldini, Stefano; Liao, Mingsheng; Zhang, Lu; Lombardini, Fabrizio; Balz, Timo; Haala, Norbert; Ding, Xiaoli; Hanssen, RamonThis paper reports on the activities carried out in the context of “Dragon project 32278: Three- and Four-Dimensional Topographic Measurement and Validation”. The research work was split into three subprojects and encompassed several activities to deliver accurate characterization of targets on land surfaces and deepen the current knowledge on the exploitation of Synthetic Aperture Radar (SAR) data. The goal of Subproject 1 was to validate topographic mapping accuracy of various ESA, TPM, and Chinese satellite system on test sites in the EU and China; define and improve validation methodologies for topographic mapping; and develop and setup test sites for the validation of different surface motion estimation techniques. Subproject 2 focused on the specific case of spatially and temporally decorrelating targets by using multi-baseline interferometric (InSAR) and tomographic (TomoSAR) SAR processing. Research on InSAR led to the development of robust retrieval techniques to estimate target displacement over time. Research on TomoSAR was focused on testing or defining new processing methods for high-resolution 3D imaging of the interior of forests and glaciers and the characterization of their temporal behavior. Subproject 3 was focused on near-real-time motion estimation, considering efficient algorithms for the digestion of new acquisitions and for changes in problem parameterization.Item Open Access Individual tree detection in urban ALS point clouds with 3D convolutional networks(2022) Schmohl, Stefan; Narváez Vallejo, Alejandra; Sörgel, UweSince trees are a vital part of urban green infrastructure, automatic mapping of individual urban trees is becoming increasingly important for city management and planning. Although deep-learning-based object detection networks are the state-of-the-art in computer vision, their adaptation to individual tree detection in urban areas has scarcely been studied. Some existing works have employed 2D object detection networks for this purpose. However, these have used three-dimensional information only in the form of projected feature maps. In contrast, we exploited the full 3D potential of airborne laser scanning (ALS) point clouds by using a 3D neural network for individual tree detection. Specifically, a sparse convolutional network was used for 3D feature extraction, feeding both semantic segmentation and circular object detection outputs, which were combined for further increased accuracy. We demonstrate the capability of our approach on an urban topographic ALS point cloud with 10,864 hand-labeled ground truth trees. Our method achieved an average precision of 83% regarding the common 0.5 intersection over union criterion. 85% percent of the stems were found correctly with a precision of 88%, while tree area was covered by the individual tree detections with an F1 accuracy of 92%. Thereby, we outperformed traditional delineation baselines and recent detection networks.Item Open Access Editorial - PFG 5/2021(2021) Cramer, Michael; Kresse, Wolfgang